Measuring alcohol use across the transition to adulthood: Racial/ethnic, sexual identity, and educational differences

•The measurement invariance of alcohol use varied across key demographic groups.•Models were more invariant across groups during adolescence than adulthood.•The alcohol use measure operated differently for youth and young adults.•Most longitudinal comparisons were scalar non-invariant; half were metric invariant.•Alcohol use measures that are non-invariant across groups or time may bias results.

BackgroundPatterns of alcohol use change from adolescence to adulthood and may differ based on race/ethnicity, sexual identity, and education. If alcohol use measures do not operate consistently across groups and developmental periods, parameter estimates and conclusions may be biased.ObjectivesTo test the measurement invariance of a multi-item alcohol use measure across groups defined by race/ethnicity, sexual identity, and college education during the transition to adulthood.MethodsUsing three waves from the National Longitudinal Study of Adolescent to Adult Health, we tested configural, metric, and scalar invariance of a 3-item alcohol use measure for groups defined by race/ethnicity, sexual identity, and college education at three points during the transition to adulthood. We then assessed longitudinal measurement invariance to test the feasibility of modeling developmental changes in alcohol use within groups defined by these characteristics.ResultsOverall, findings confirm notable variability in the construct reliability of a multi-item alcohol use measure during the transition to adulthood. The alcohol use measure failed tests of metric and scalar invariance, increasingly across ages, both between- and within-groups defined by race/ethnicity, sexual identity, and college education, particularly among females.ConclusionsMeasurement testing is a critical step when utilizing multi-item measures of alcohol use. Studies that do not account for the effects of group or longitudinal measurement non-invariance may be statistically biased, such that recommendations for risk and prevention efforts could be misguided.